Abstract
This paper performs a global robust stability analysis of a particular class of hybrid bidirectional associative memory time-varying delayed neural network with norm-bounded timevarying parameter uncertainties. The activation functions are assumed to be globally Lipschitz continuous. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing relaxation matrices which, when chosen properly, produce a less conservative result. Two numerical examples are given to illustrate the significant improvement obtained in the conservativeness of the delay bound.
| Original language | English |
|---|---|
| Pages (from-to) | 164-171 |
| Number of pages | 8 |
| Journal | Journal of Marine Science and Technology |
| Volume | 18 |
| Issue number | 2 |
| Publication status | Published - 2010 Apr 1 |
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All Science Journal Classification (ASJC) codes
- Oceanography
- Ocean Engineering
- Mechanics of Materials
- Mechanical Engineering
Cite this
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A delay-dependent approach to robust stability for uncertain hybrid bidirectional associative memory neural networks with time-varying delays. / Lu, Chien-Yu; Chang, Koan Yuh; Tsai, Hsun Heng; Chang, Wen Jer.
In: Journal of Marine Science and Technology, Vol. 18, No. 2, 01.04.2010, p. 164-171.Research output: Contribution to journal › Article
TY - JOUR
T1 - A delay-dependent approach to robust stability for uncertain hybrid bidirectional associative memory neural networks with time-varying delays
AU - Lu, Chien-Yu
AU - Chang, Koan Yuh
AU - Tsai, Hsun Heng
AU - Chang, Wen Jer
PY - 2010/4/1
Y1 - 2010/4/1
N2 - This paper performs a global robust stability analysis of a particular class of hybrid bidirectional associative memory time-varying delayed neural network with norm-bounded timevarying parameter uncertainties. The activation functions are assumed to be globally Lipschitz continuous. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing relaxation matrices which, when chosen properly, produce a less conservative result. Two numerical examples are given to illustrate the significant improvement obtained in the conservativeness of the delay bound.
AB - This paper performs a global robust stability analysis of a particular class of hybrid bidirectional associative memory time-varying delayed neural network with norm-bounded timevarying parameter uncertainties. The activation functions are assumed to be globally Lipschitz continuous. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing relaxation matrices which, when chosen properly, produce a less conservative result. Two numerical examples are given to illustrate the significant improvement obtained in the conservativeness of the delay bound.
UR - http://www.scopus.com/inward/record.url?scp=77952350235&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77952350235&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:77952350235
VL - 18
SP - 164
EP - 171
JO - Journal of Marine Science and Technology
JF - Journal of Marine Science and Technology
SN - 1023-2796
IS - 2
ER -